3 Sequencing data
3.1 Sequencing depth
tibble(metric=c("Total GB", "Total reads", "Average GB", "Average reads"),
value=unlist(c(round(all_data %>% summarise(sum(bases_pre_fastp)) / 1000000000,2),
round(all_data %>% summarise(sum(bases_pre_fastp)) / 300,2),
paste0(round(all_data %>% summarise(mean(bases_pre_fastp)) / 1000000000,2),"±",round(all_data %>% summarise(sd(bases_pre_fastp)) / 1000000000,2)),
paste0(round(all_data %>% summarise(mean(bases_pre_fastp)) / 300,0),"±",round(all_data %>% summarise(sd(bases_pre_fastp)) / 300,0))))
) %>%
tt()| metric | value |
|---|---|
| Total GB | 937.37 |
| Total reads | 3124578099 |
| Average GB | 5.18±2.46 |
| Average reads | 17262862±8195554 |
all_data %>%
group_by(Taxon,Extraction) %>%
summarise(value = sprintf("%.1f±%.1f", mean(bases_post_fastp / 1000000000), sd(bases_post_fastp / 1000000000))) %>%
pivot_wider(names_from = Extraction, values_from = value) %>%
tt(caption = "Mean and standard deviation of sequencing depth (GB)")| Taxon | DREX | EHEX | ZYMO |
|---|---|---|---|
| Amphibian | 3.2±2.1 | 4.7±0.3 | 4.0±1.6 |
| Bird | 4.2±2.4 | 3.1±1.9 | 3.9±1.8 |
| Control | 0.5±0.6 | 2.1±2.7 | 0.0±0.0 |
| Mammal | 4.6±2.0 | 3.8±2.2 | 5.4±3.2 |
| Reptile | 5.7±1.3 | 5.0±1.8 | 6.1±2.2 |
all_data %>%
ggplot(aes(x=Extraction,y=bases_pre_fastp))+
geom_boxplot() +
facet_grid(. ~ Taxon, scales = "free") +
labs(y="DNA yield (ng)",x="Extraction method")all_data %>%
filter(Taxon != "Control") %>%
lmerTest::lmer(bases_post_fastp ~ Extraction + (1 | Sample) + (1 | Species), data = ., REML = FALSE) %>%
broom.mixed::tidy() %>%
tt()| effect | group | term | estimate | std.error | statistic | df | p.value |
|---|---|---|---|---|---|---|---|
| fixed | NA | (Intercept) | 4322719741 | 382290022 | 11.30743545 | 1.711860e+01 | 2.299227e-09 |
| fixed | NA | ExtractionEHEX | 10864597 | 284400639 | 0.03820173 | 1.443429e+09 | 9.695268e-01 |
| fixed | NA | ExtractionZYMO | 485437083 | 283030980 | 1.71513762 | 4.313942e+21 | 8.632000e-02 |
| ran_pars | Sample | sd__(Intercept) | 1407267694 | NA | NA | NA | NA |
| ran_pars | Species | sd__(Intercept) | 508228833 | NA | NA | NA | NA |
| ran_pars | Residual | sd__Observation | 1524168473 | NA | NA | NA | NA |
3.2 Quality-filtering
all_data %>%
mutate(qf_bases=bases_post_fastp/bases_pre_fastp*100) %>%
group_by(Taxon,Extraction) %>%
summarise(value = sprintf("%.1f±%.1f", mean(qf_bases), sd(qf_bases))) %>%
pivot_wider(names_from = Extraction, values_from = value) %>%
tt(caption = "Mean and standard deviation of quality-filtered proportion of reads")| Taxon | DREX | EHEX | ZYMO |
|---|---|---|---|
| Amphibian | 91.7±3.7 | 87.6±2.9 | 84.7±1.2 |
| Bird | 70.3±23.0 | 70.2±14.7 | 70.9±16.1 |
| Control | 9.8±11.5 | 27.5±3.4 | 3.3±2.3 |
| Mammal | 89.5±4.7 | 91.2±1.9 | 91.9±2.3 |
| Reptile | 90.5±7.1 | 88.3±7.2 | 89.9±6.3 |
all_data %>%
mutate(qf_bases=bases_post_fastp/bases_pre_fastp*100) %>%
ggplot(aes(x=Extraction,y=qf_bases))+
geom_boxplot() +
facet_grid(. ~ Taxon, scales = "free") +
labs(y="DNA yield (ng)",x="Extraction method")all_data %>%
mutate(qf_bases=bases_post_fastp/bases_pre_fastp*100) %>%
filter(Taxon != "Control") %>%
lmerTest::lmer(qf_bases ~ Extraction + (1 | Sample) + (1 | Species), data = ., REML = FALSE) %>%
broom.mixed::tidy() %>%
tt()| effect | group | term | estimate | std.error | statistic | df | p.value |
|---|---|---|---|---|---|---|---|
| fixed | NA | (Intercept) | 84.867885 | 3.229677 | 26.2775145 | 12.92142 | 1.337096e-12 |
| fixed | NA | ExtractionEHEX | -1.238440 | 1.268390 | -0.9763877 | 145.71392 | 3.304905e-01 |
| fixed | NA | ExtractionZYMO | -1.811218 | 1.262245 | -1.4349184 | 145.69071 | 1.534536e-01 |
| ran_pars | Sample | sd__(Intercept) | 7.418801 | NA | NA | NA | NA |
| ran_pars | Species | sd__(Intercept) | 9.356829 | NA | NA | NA | NA |
| ran_pars | Residual | sd__Observation | 6.797395 | NA | NA | NA | NA |